When you choose to run your business on Google Cloud you benefit from the same planet-scale infrastructure that powers Google’s products such as Maps, YouTube, and Workspace. 

We have picked 10 ways in which Google Cloud Infrastructure services outshine alternatives in the market in how they simplify your operations, save money, and secure your data. 

1. Custom Machine Types means no wasted resources

Compute Engine offers predefined machine types that you can use when you create a VM instance. A predefined machine type has a preset number of vCPUs and a preset amount of memory; each type is billed at a set price as described on the Compute Engine pricing page. 

If predefined machine types don’t meet your needs, you can create a VM instance with a custom number of vCPUs and custom amount of memory, effectively building a custom machine type. Custom machine types are available only for general-purpose machine families. When you create a custom machine type, you are deploying a custom machine type from the E2, N2, N2D, or N1 machine family on GCP.  No other leading cloud vendor offers custom machine types so extensively.

Custom machine types are a good idea for workloads that aren’t a good fit for the predefined machine types and for workloads that require more processing power or memory but don’t need all of the upgrades provided by the next machine type level. This translates into lower operating costs.   They are also useful for controlling software licensing costs that are based on the number of underlying compute cores. 

Jeremy Lloyd, Infrastructure and Application Modernization Lead at Appsbroker, a Google partner: 

“Custom machine types coupled with Google’s StratoZone data center discovery tool provides Appsbroker with the flexibility we need to provide cost efficient virtual machines matched to a virtual machine’s actual utilization. As a result, we are able to keep our customers’ operating costs low while still providing the ability to scale as needed.”

2. Compute Engine Virtual Machines are optimized for scale-out workloads 

For scale-out workloads, T2D, the first instance type in the Tau VM family, is based on 3rd Gen AMD EPYC processors and leapfrogs VMs for scale-out workloads of any leading public cloud provider today, both in terms of performance and price-performance. Tau VMs offer 56% higher absolute performance and 42% higher price-performance compared to general-purpose VMs from any leading public cloud vendor (source). The x86 compatibility provided by these AMD EPYC processor-based VMs gives you market-leading performance improvements and cost savings, without having to port your applications to a new processor architecture. Sign up here  if you are interested in trying out T2D instances in Preview. 

For SAP HANA, Google Cloud has demonstrated with SAP how we can run the world’s largest scale-out HANA system in the public cloud (96TB).   With such innovation, you are covered as your business grows exponentially.

3. Largest single node GPU-enabled VM

Google is the only public cloud provider to offer up to 16 NVIDIA A100 GPUs in a single VM, making it possible to train very large AI models. Users can start with one NVIDIA A100 GPU and scale to 16 GPUs without configuring multiple VMs for single-node ML training, without crossing the VM layer. 

Additionally, customers can choose smaller GPU configurations—1, 2, 4 and 8 GPUs per VM—providing the flexibility to scale their workload as needed. 

The A2 VM family was designed to meet today’s most demanding applications—workloads like CUDA-enabled machine learning (ML) training and inference, for example. This family is built on the A100 GPU which offers up to 20x the compute performance compared to the previous generation GPU and comes with 40 GB of high-performance HBM2 GPU memory. To speed up multi-GPU workloads, the A2 VMs use NVIDIA’s HGX A100 systems to offer high-speed NVLink GPU-to-GPU bandwidth that delivers up to 600 GB/s. A2 VMs come with up to 96 Intel Cascade Lake vCPUs, optional Local SSD for workloads requiring faster data feeds into the GPUs and up to 100 Gbps of networking. A2 VMs provide full vNUMA transparency into the architecture of underlying GPU server platforms, enabling advanced performance tuning. Google Cloud offers these GPUs globally. 

4. ​​Non-disruptive maintenance means you worry less about planned downtime

Compute Engine offers live migration (non-disruptive maintenance) to keep your virtual machine instances running even when a host system event, such as a software or hardware update, occurs. Google’s Compute Engine live migrates your running instances to another host in the same zone without requiring your VMs to be rebooted. Live migration enables Google to perform maintenance that is integral to keeping infrastructure protected and reliable without interrupting any of your VMs. When a VM is scheduled to be live-migrated, Google provides a notification to the guest that a migration is imminent. 

Live migration keeps your instances running during:

• Regular infrastructure maintenance and upgrades
• Network and power grid maintenance in the data centers
• Failed hardware such as memory, CPU, network interface cards, disks, power, and so on. This is done on a best-effort basis; if a hardware component fails completely or otherwise prevents live migration, the VM crashes and restarts automatically and a hostError is logged.
• Host OS and BIOS upgrades
• Security-related updates
• System configuration changes, including changing the size of the host root partition, for storage of the host image and packages

Live migration does not change any attributes or properties of the VM itself. The live migration process transfers a running VM from one host machine to another host machine within the same zone. All VM properties and attributes remain unchanged, including internal and external IP addresses, instance metadata, block storage data and volumes, OS and application state, network settings, network connections, and so on. This has the benefit of reducing operational and maintenance overhead, helps you build a more robust security posture where infrastructure can be consciously revamped from a known good state and minimizes risks for advanced persistent threats. 

Refer to Lessons learned from a year of using live migration in production on Google Cloud from the Google engineering team.

5. Trusted Computing: Shielded VMs guard you against advanced, persistent attacks

Establishing trust in your environment is multifaceted, involving hardware and firmware, as well as host and guest operating systems. Unfortunately, threats like boot malware or firmware rootkits can stay undetected for a long time, and an infected virtual machine can continue to boot in a compromised state even after you’ve installed legitimate software. 

Shielded VMs can help you protect your system from attack vectors like:

• Malicious guest OS firmware, including malicious UEFI extensions
• Boot and kernel vulnerabilities in the guest OS
• Malicious insiders within your organization

To guard against these kinds of advanced persistent attacks, Shielded VMs use:

• Unified Extensible Firmware Interface (UEFI) BIOS: Helps ensure that firmware is signed and verified
• Secure and Measured Boot: Helps ensure that a VM boots an expected, healthy kernel
• Virtual Trusted Platform Module (vTPM): Establishes root-of-trust, underpins Measured Boot, and prevents exfiltration of vTPM-sealed secrets
• Integrity Monitoring: Provides tamper-evident logging, integrated with Stackdriver, to help you quickly identify and remediate changes to a known integrity state

The Google approach allows customers to deploy Shielded VMs with only a simple click, thereby easing implementation. 

6. Confidential Computing encrypts data while in use

Google Cloud was a founding member of the Confidential Computing Consortium. Along with encryption of data in transit and at rest using customer-managed encryption keys (CMEK) and customer-supplied encryption keys (CSEK), Confidential VM adds a “third pillar” to the end-to-end encryption story by encrypting data while in use. Confidential Computing uses processor-based technology that allows data to be encrypted in use while it is being processed in the public cloud. Confidential VM allows you to to encrypt memory in use on a Google Compute Engine VM by checking a single checkbox. 

All Confidential VMs support the previously mentioned Shielded VM features under the covers—you can think of Shielded VM as helping to address VM integrity, while Confidential VM addresses the memory encryption aspect which relies on CPU features. With the confidential execution environments provided by Confidential VM and AMD Secure Encrypted Virtualization (SEV), Google Cloud keeps customers’ sensitive code and other data encrypted in memory during processing. Google does not have access to the encryption keys. In addition, Confidential VM can help alleviate concerns about risk related to either dependency on Google infrastructure or Google insiders’ access to customer data in the clear. 

See what Google Cloud partners say about Confidential Computing here. 

7. Advanced networking delivers full-stack networking and security services with fast, consistent, and scalable performance

Google Cloud’s network delivers low latency, reduces operational costs and ensures business continuity, enabling organizations to seamlessly scale up or down in any region to meet business needs. Our planet-scale network uses advanced software-defined networking and security with edge caching services to deliver fast, consistent, and scalable performance. With 28 regions, 85 zones, and 146 PoPs connected by 16 subsea fiber cables around the world, Google Cloud’s network offers a full stack of layer 1 to layer 7 services for enterprises to run their workloads anywhere. Enterprises can be assured that they have best-in-class networking and security services connecting their VMs, containers, and bare metal resources in hybrid and multi-cloud environments with simplicity, visibility, and control. 

Google Cloud’s network has protected customers from one of the world’s largest DDoS attacks at 2.54 Tbps. With our multi-layer security architecture and products such as Cloud Armor, our customers ran their business with no disruptions. Furthermore, our recent integration of Cloud Armor with reCAPTCHA Enterprise adds best-in-class bot and fraud management to prevent volumetric attacks. Cloud Armor is deployed with our Cloud Load Balancer and Cloud CDN, extending the secure benefits at the network edge for traffic coming into Google Cloud so customers have security, performance, and reliability all built in. Furthermore, we are excited to offer Cloud IDS in preview, which was co-developed with security industry leader, Palo Alto Networks, to run natively in Google Cloud. 

Our advanced networking capabilities also extends to GKE and Anthos networking. With the GKE Gateway controller, customers can manage internal and external HTTPS load balancing for a GKE cluster or a fleet of GKE clusters with multi-tenancy while maintaining centralized admin policy and control. Unlike other Kubernetes offerings, we offer eBPF dataplane which brings powerful tooling such as Kubernetes network policy and logging to GKE. eBPF is known to kernel engineers as a “superpower” for its unique architecture to load and unload modules in kernel space, and now this capability is built in with Google Cloud networking. 

For observability and monitoring, our customers deploy Network Intelligence Center, Google Cloud’s comprehensive network monitoring, verification and optimization platform. With four key modules in Network Intelligence Center, and several more to come, we are working towards realizing our vision of proactive network operations that can predict and heal network failures, driven by AI/ML recommendations and remediation. Network Intelligence Center provides unmatched visibility into your network in the cloud along with proactive network verification. Centralized monitoring cuts down troubleshooting time and effort, increases network security and improves the overall user experience.  

8. Regional Persistent Disk for High Availability

Regional Persistent Disk is a storage option that provides synchronous replication of data between two zones in a region. Regional Persistent Disks can be a great building block if you need to ensure high availability of your critical applications as they offer cost-effective durable storage and replication of data between two zones in the same region. 

Regional Persistent Disks are also easy to set up within the Google Cloud Console. If you are designing robust systems or high availability services on Compute Engine, Regional Persistent Disks combined with other best practices such as backing up your data using snapshots enable you to build an infrastructure that is highly available and recoverable in a disaster. Regional Persistent Disks are also designed to work with regional managed instance groups. In the unlikely event of a zonal outage, Regional Persistent Disks allow continued I/O through failover of your workloads to another zone. Regional Persistent Disks can help meet zero RPO and near-zero RTO requirements and other stringent SLAs that your critical applications might require by maximizing application availability and protection of data during events such as host/VM failures and zonal outages. 

9. Cloud Storage’s single namespace for dual-region and multi-region means managing regional replication is incredibly simple

Similar to how Persistent Disk makes data more available by replicating data across zones, Cloud Storage provides similar benefits for object storage. Cloud Storage within a region is cross-zone by definition, reducing the risk that a zonal outage would take down your application. Cloud Storage adds to this by also providing a cross-region option that can protect against a regional outage and gets your data closer to distributed users. This comes in the form of Dual-region or Multi-region settings for a bucket. These are the simplest to implement cross-region replication offerings in the industry—just a simple button or API call to enable them. In addition to being simple to implement, they offer an added advantage of using a single bucket name that spans regions. 

This is unique in the industry. Competitive offerings currently require setting up and managing two distinct buckets, one in each region and they don’t offer the strong consistency properties Cloud Storage offers across regions. Operations and app development are burdened by this design. Google’s single namespace approach dramatically simplifies application development (the app runs on single region or dual/multi-region without any changes), and provides simpler application restarts and testing for DR.

10. Predictive autoscaling 

Customers use predictive autoscaling to improve response times for applications with long initialization times or for applications with workloads that vary predictably with daily or weekly cycles. When you enable predictive autoscaling, Compute Engine forecasts future load based on your Managed Instance Group’s history and scales out the MIG’s in advance of predicted load, so that new instances are ready to serve when the load arrives. Without predictive autoscaling, an autoscaler can only scale a group reactively, based on observed changes in load in real time. 

With predictive autoscaling enabled, the autoscaler works with real-time data as well as with historical data to cover both the current and forecasted load. Forecasts are refreshed every few minutes (faster than competing clouds) and consider daily and weekly seasonality, leading to more accurate forecasts of load patterns.

For more information, see How predictive autoscaling works and Checking if predictive autoscaling is suitable for your workload.

These are just a few examples of customer-centric innovation that set Google Cloud infrastructure apart.  Bring your applications and let the platform work for you.   

Get started by learning about your options for migration, or talk to our sales team to join the thousands of customers who have embarked upon this journey.

Acknowledgement

Special thanks to Dheeraj Konidena (Google) for contributing to this article.

In previous blog posts, we’ve discussed the benefits that organizations can reap by measuring and then optimizing their overall ESG impact. In this post, we’ll look at the endgame: sustainable transformation into an organization that continually adapts to maximize its resilience while reducing risk. Where will my customers be with the evolving global community landscape? How can I design communities and products with sustainability in mind? Are my assets exposed to physical climate risk — drought, flood, wildfire? Adaptation and resilience are the board and legislative focus areas that the ambition loops created by Google Cloud Ready – Sustainability seek to accelerate. 

This is especially important due to the scrutiny of governments and financial institutions as they evaluate the viability of physical asset investments. These organizations want assurances that their investments will not be under undue environmental risk. Similarly, companies embarking on net-zero transitions can realize interest expense savings by providing the measurable, accountable assurances their financiers demand.

Leveraging analytics for climate and business resilience

We’ve said it before, but it bears repeating: The Google Cloud Ready – Sustainability program challenges the notion that sustainability is just a nice-to-have or merely good PR. Rather, we designed the program to help organizations adapt to a net-zero future with solutions that reduce risk, support growth, provide competitive advantages, and positively impact the bottom line. The following partners provide data and analytics that offer deep insights into the environment, natural resources, and social trends that point the way toward sustainable, profitable growth. 

Atlas AI has built a geospatial artificial intelligence platform that helps every organization anticipate changing societal conditions — where people live, where wealth and poverty are concentrated, how the physical makeup of communities is evolving, and more — to determine where to invest today to prepare for the world of tomorrow. Atlas AI customers, which range from the World Bank and global NGOs to multinational corporations, use the platform to accelerate growth, future-proof supply chains, target resources to vulnerable populations, and build greater resilience to climate change.  

Climate Engine’s SpatiaFi solution, powered by Google Cloud, helps financial services organizations connect economic assets to the world of Earth observation data supporting regulatory reporting, climate risk reduction, and new innovative sustainable finance offerings. Combining billions of planetary observations with peer-reviewed scientific methods, SpatiaFi is connecting Earth science to operational systems offering new levels of accuracy, transparency, scalability, and trust in climate and sustainability data in the context of financial decision-making.

Kumi Analytics‘ KACSAT solution was approved by OxCarbon as a methodology for the calculation and verification of voluntary carbon offsets in support of nature-based solutions. KACSAT leverages multiple satellite platforms and Google Earth Engine‘s state-of-the-art processing tools to enable science-based carbon assessment aligned to the Oxford Offsetting Principles of environmental integrity, additionality, permanence, and achieving net-zero emissions. Environmental organizations, financial institutions, and corporations can now offset their carbon footprints through the reforestation and conservation of millions of hectares of forests — something that was previously limited due to the cost and time of validating high-quality forest projects.

Tensorflight revolutionizes property underwriting with AI. Its cutting-edge tool provides underwriters and insurers with access to rich and highly accurate datasets for commercial and residential properties, enabling them to create superior insurance products. As pioneers of the first property-inspection platform based on convolutional neural networks, Tensorflight’s advanced technology connects seamlessly via API and utilizes ground-level imagery, satellite, and aerial data. This unique approach enables the company to generate precise replacement costs and conduct more comprehensive risk assessments. By automating property inspections and enhancing underwriting accuracy, Tensorflight empowers insurance providers to plan for the future with pragmatic decision-making. With Tensorflight, the future of property underwriting is transformed, offering unparalleled insights, efficiency, and sustainability.

Are you ready for sustainability transformation?

Transforming into a net-zero organization means much more than building resilience to climate change, as important as that is. It also means finding the customers of the future, achieving ongoing energy savings, more sustainable resource usage, and improved transparency to regulatory institutions and consumers. Google Cloud Ready – Sustainability partners offer certified solutions that can help organizations get there.

Look for Google Cloud Ready – Sustainability validated solutions on the Google Cloud Partner Directory Listing, Google Cloud Ready Sustainability Partner Advantage page, and — if applicable — via the Google Cloud Marketplace. We hope to help customers better understand how these technologies can help them meet their ESG goals, find the right solutions for their particular challenges, and implement solutions faster. 

Learn more about the Google Cloud Ready – Sustainability validation initiative and explore all our partners in sustainability transformation.

The Google Cloud console is a powerful platform that lets users manage their cloud projects end-to-end with an intuitive web-based UI. With over 120 Google Cloud products across thousands of pages, it can be challenging to navigate through the console quickly, and many users don’t like to use the command line interface. To help, Google Cloud console team recently made several improvements to our search and navigation features, making it easier to find what you need, when you need it.

The Cloud console’s search dropdown and result page

Expanded resource-type search

One of the most significant improvements to the console’s search feature is the increased resource-type coverage. You can now find instances of nearly all of the over 120 products that Google Cloud offers directly from the search bar, rather than by manually clicking to the details section nested within specific product pages. This wider coverage saves you time compared to browsing through the different product categories to find what you’re looking for. This improvement also allows the console experience team to continuously add new resource types as we develop new features and capabilities in our various product offerings.

Search for more than 90 types of resources using Google Cloud console

Improved documentation search

We also improved the coverage and accuracy of the search experience for documentation, making it easier to find specific pages or interactive tutorials. Developers looking to get started with something they’re unfamiliar with may want to undertake tutorials in the context of their own working environment. Even experienced developers just looking for a quick answer to their question may not want to leave the console, so we expect these improvements can help users of all experience levels.

We’ve heard from you that finding the right documentation from within the console can be tricky, and so we hope this change can save you from needing to switch over to web search to be confident that they’ll find what you’re looking for.

Cloud documentation and tutorials are available for search in the console

A refreshed search results page

To make browsing search results easier, we also overhauled our search results page by dividing results into tabs, similar to Google web search. This means that you can refine your search by diving into one of those categories individually. In addition to maintaining an “all results” tab, there are tabs for:

• Documentation and tutorials
• Resource instances, and
• Marketplace and APIs

Each tab also has a better filtering experience that’s unique to that search result category. For instance, the Resources tab lets you filter by metadata like the last time a resource was interacted with, while the Documentation tab allows you to search for interactive tutorials only. If you can’t find what you’re looking for in the autocomplete dropdown, try the search results page. It can provide additional results or context to help you find exactly what you’re looking for.

The Resources tab lists results in a denser, metadata-rich format with filtering available

Accurate industry-wide synonyms

Google Cloud console search now interprets industry-wide synonyms accurately — if you’re coming from AWS or Azure and know the name of a product in that ecosystem, searching for it will return the Google Cloud equivalent. A full list of synonyms can be found here. 

General usability improvements

We also shipped several smaller quality-of-life improvements related to search, including:

• Improvements to accessibility, including better color contrast and zoom behaviors
• Faster latency targets and shorter load times for results
• A search keyboard shortcut — just type “/” to begin searching without using your mouse
• The ability to search for an API resource by its key

 We also updated the look and feel of our platform bar to a cleaner, more modern experience that’s more in line with the branding across other Google Cloud interfaces.

Google Cloud console’s old platform bar (top) and the updated version (bottom)

A customizable navigation menu

Finally, we made usability improvements to the left-hand navigation menu by allowing you to pin specific products. Products can be pinned from the left nav menu or our brand new All Product Page. This is a shift away from the default ordering of products that attempted a “one size fits all” approach to navigation. This customization feature lets you tailor the console to your specific needs and work more efficiently.

Products can be pinned to the left nav menu for easy access

Final thoughts

The Google Cloud console’s navigation and search features have come a long way. With these recent improvements, you can find what you need quickly and efficiently, making it easier to manage your cloud resources. From expanded resource-type search to improved documentation search and refined search results, the console is more user-friendly than ever before.

We are excited to announce that Google has been named a Leader in The Forrester Wave™: Streaming Analytics, Q2 2021 report. Thank you to our strong community of customers and partners for working with us to deliver a customer focused product. We believe Forrester’s recognition is an acknowledgement of our leadership across an integrated set of capabilities that rely on data to drive transformation. We were also honored to be named a leader in The Forrester Wave™: Cloud Data Warehouse, Q1 2021. 

Forrester gave Dataflow a score of 5 out of 5 across 12 different criteria and according to the report: “Google Cloud Dataflow has strengths in data sequencing, advanced analytics, performance, and high-availability. Google Dataflow’s sweet spot is for enterprises that have a preponderance of real-time data generated on Google Cloud Platform or wish to simplify all data processing by using a single platform that unifies both streaming and batch jobs.” 

Harnessing the power of real-time data

The speed with which businesses are able to respond to change is the difference between those that successfully navigate the future and those that get left behind. In order to accelerate their digital transformation, reimagine their business and leverage the power of real-time data,  today’s data leaders require a streaming analytics platform that provides both depth and breadth.  

Cloud Pub/Sub and Cloud Dataflow, based on more than a decade of experience in internet scale systems for Google’s own needs, provide customers with a reliable, scalable, performant platform. In addition, we’ve designed these products for ease of use to make streaming analytics accessible to more users, which is why customers such as Sky and others from across all industries use Dataflow to run streaming analytics workloads.

5 out of 5 across key streaming analytics criteria

While Forrester gave Dataflow a score of 5 out of 5 in 12 criteria, the product achieved the highest possible scores in areas that are top of mind for our customers.

We continue to be focused on solving problems that matter to you. For example, just in the last month we announced Dataflow Prime and  Auto Sharding for BigQuery – two new auto tuning capabilities that bring efficiency and simplicity to your streaming pipelines. 

Dataflow achieves highest score possible in strategy 

With Google, organizations gain an industry leading product and a partner that has the vision and strategy to help you tackle new business challenges and provide delightful experiences to your customers.

In summary, we are honored to be a Leader in The Forrester Wave™, Streaming Analytics, and look forward to continuing to innovate and partner with you on your digital transformation journey. 

Download the full report: The Forrester Wave™: Streaming Analytics, Q2 2021 and check out these smart analytics reference patterns. To learn more about Dataflow, visit our website and get to know the product by taking an interactive tutorial. You can also watch recordings from the Data Cloud Summit event (May 2021), where we provided an in-depth view of new product innovations in Dataflow and other data analytics products.